# Deezer Scraper - Tracks, Artists & Albums (`benthepythondev/deezer-scraper`) Actor Search Deezer for tracks, artists or albums by keyword and get structured data: title/name, artist, album, duration, rank/popularity, release date, cover image, preview and link. Fast and reliable via the public Deezer API. For music research, catalogs and apps. - **URL**: https://apify.com/benthepythondev/deezer-scraper.md - **Developed by:** [ben](https://apify.com/benthepythondev) (community) - **Categories:** Videos, Business, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 🎵 Deezer Scraper Search **Deezer** for **tracks**, **artists** or **albums** by keyword and get clean, structured data — title/name, artist, album, duration, rank/popularity, release date, cover image, preview and link. Powered by the public Deezer API, so it's fast and reliable: no browser, no login, no API key. Built for music research, catalog building, playlist tools and apps. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n. ### 🔎 What is the Deezer Scraper? Give it keywords (e.g. "daft punk", "lofi") and it returns matching tracks, artists or albums as structured rows — switch type with one setting. Great for finding music by query and building a clean dataset. #### What data does it extract? - **Tracks**: title, artist, album, duration, rank, explicit flag, preview, link - **Artists**: name, fans, album count, picture, link - **Albums**: title, artist, track count, release date, cover, link ### ⬇️ Input | Field | Type | Description | |-------|------|-------------| | `searchTerms` | array | Keywords to search, e.g. `daft punk`. | | `searchType` | string | `track`, `artist` or `album`. | | `maxPerTerm` | integer | Max results per term. Default `30`. | #### Example input ```json { "searchTerms": ["daft punk"], "searchType": "track", "maxPerTerm": 50 } ```` ### ⬆️ Output One record per track: ```json { "type": "track", "id": 3135556, "title": "Get Lucky", "artist": "Daft Punk", "artist_id": 27, "album": "Random Access Memories", "duration_sec": 369, "rank": 856724, "explicit": false, "preview": "https://cdn-preview.deezer.com/.../preview.mp3", "cover": "https://.../cover_xl.jpg", "link": "https://www.deezer.com/track/3135556", "query": "daft punk" } ``` ### 💡 Use cases - 🎧 **Music research** — find tracks, artists and albums by query. - 📊 **Catalogs & datasets** — build a structured music database. - 🎛️ **Playlist & app tools** — enrich titles with metadata and previews. - 🤖 **LLM / app pipelines** — feed structured music data into your tools. ### ❓ FAQ **Do I need an API key or login?** No — it uses the public Deezer API. **Tracks, artists and albums?** Yes — set `searchType`. **Do I get a preview?** Yes — a preview URL for tracks. **Are cover images included?** Yes — high-resolution cover/picture URLs. **How many can I get?** Set `maxPerTerm` — it paginates automatically. **How does pricing work?** Pay per result returned. No subscription. **Is it legal?** It uses the public Deezer API. Audio/content belongs to rights holders — use responsibly and within Deezer's terms. ### ⚙️ How it works The scraper calls the Deezer search API directly and returns clean rows — no browser and no key. It paginates through results, de-duplicating as it goes, and normalizes each track, artist or album into consistent fields. Runs are fast and dependable, which is why the actor keeps passing its daily health check. The same input shape works for a quick top-10 or a deep multi-term sweep — only `maxPerTerm` changes. ### 👥 Who uses music data? Music data is valuable to app developers, marketers, researchers and creators. A developer enriches a playlist app with metadata and previews; a marketer studies what's popular in a genre; a researcher builds a music dataset; a creator finds reference tracks. Because every record is plain JSON with consistent fields, it drops straight into a spreadsheet, database, BI tool or LLM pipeline with no custom parsing. ### 📤 Export, schedule & integrate Every run is saved to a dataset you can export to **JSON, CSV, Excel, XML or RSS**, or pull through the **Apify API**. Wire it into **Make, Zapier, n8n, Google Sheets, Slack** or your **own database**, run it on a **schedule** to keep your data fresh, and call it from AI agents through the **Apify MCP server**. ### 💡 Tips for best results - Search an artist name with `searchType: album` to map a discography. - Use `rank` to sort tracks by popularity in your spreadsheet. - Combine several queries in one run to build a genre dataset. - Schedule runs to track new releases for an artist. ### ❓ More FAQ **How fresh is the data?** It is fetched live on each run. **Can I run it automatically?** Yes — use Apify Schedules (cron). **Which export formats?** JSON, CSV, Excel, XML and RSS, plus the Apify API. **Can AI agents use it?** Yes — via the Apify API and MCP server. ### 🔗 You might also like - [TheSportsDB Scraper](https://apify.com/benthepythondev/thesportsdb-scraper) — teams & players. - [Steam Games Scraper](https://apify.com/benthepythondev/steam-games-scraper) — game prices & metadata. - [TV Shows Scraper](https://apify.com/benthepythondev/tvmaze-tv-shows-scraper) — TV series & episodes. *** **Keywords:** deezer scraper, deezer api, music data, track data, artist data, album data, music metadata, music research, song scraper, music catalog, music dataset, music api, playlist data, deezer search # Actor input Schema ## `searchTerms` (type: `array`): Keywords to search, e.g. 'daft punk', 'lofi'. ## `searchType` (type: `string`): Tracks, artists or albums. ## `maxPerTerm` (type: `integer`): Max results per search term. ## Actor input object example ```json { "searchTerms": [ "daft punk" ], "searchType": "track", "maxPerTerm": 30 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchTerms": [ "daft punk" ], "searchType": "track" }; // Run the Actor and wait for it to finish const run = await client.actor("benthepythondev/deezer-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchTerms": ["daft punk"], "searchType": "track", } # Run the Actor and wait for it to finish run = client.actor("benthepythondev/deezer-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchTerms": [ "daft punk" ], "searchType": "track" }' | apify call benthepythondev/deezer-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=benthepythondev/deezer-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Deezer Scraper - Tracks, Artists & Albums", "description": "Search Deezer for tracks, artists or albums by keyword and get structured data: title/name, artist, album, duration, rank/popularity, release date, cover image, preview and link. Fast and reliable via the public Deezer API. For music research, catalogs and apps.", "version": "1.0", "x-build-id": "CLu5MoNXEopj1H3Hc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/benthepythondev~deezer-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-benthepythondev-deezer-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/benthepythondev~deezer-scraper/runs": { "post": { "operationId": "runs-sync-benthepythondev-deezer-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/benthepythondev~deezer-scraper/run-sync": { "post": { "operationId": "run-sync-benthepythondev-deezer-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Keywords to search, e.g. 'daft punk', 'lofi'.", "items": { "type": "string" } }, "searchType": { "title": "Search type", "enum": [ "track", "artist", "album" ], "type": "string", "description": "Tracks, artists or albums.", "default": "track" }, "maxPerTerm": { "title": "Max per term", "minimum": 1, "maximum": 300, "type": "integer", "description": "Max results per search term.", "default": 30 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```